Agent-based Modeling | Transport Modeling | Spatial Analytics
Jayita Chakraborty, PhD
Former Data Scientist | University of Leeds
Jan 12, 2026
Analysing Global Policy Responses to COVID-19
RQ: What mechanisms drive the rapid and homogeneous diffusion of lockdown policies across heterogeneous countries, and how can these mechanisms be captured through agent-based simulation?
| Attributes | Characteristics |
|---|---|
| GDP | National income per country that is read from data |
| Democracy | Democracy index per country that is read from data |
| Population Density | Average Population density per country that is read from data |
| Covid Cases | Covid Cases per thousand population (normalized on average) |
| Initial State of policy | Adopted policy measure on March 1, 2020 |
| Distance (Minimum Difference) | Key variable of the model in that defines the distance between some agent and all other agents |
| Social Threshold | A parameter incorporated to influence the policy adoption of the agent. The parameter is calculated based on the following equation: \[ ST = e^{\text{Covid Cases}} \times (\text{Base Threshold})^{2} \times \text{Lockdown Adoption Probability} \] |
Base threshold:
Peer size:
Lockdown adoption probability:
A Simulation-based assessment of demand-supply interactions for Ridesourcing services in an urban environment
High Demand
Low Demand
High Demand
Low Demand
Where do e-cargo bikes go?
Before applying algorithm
After applying algorithm